Like schoolyard picks, where team captains compete for the most promising athletes, local and state governments are left trying to find qualified data scientists that weren’t already snatched up by big tech companies.

The public sector is a huge contributor to the exponential growth of big data. And with the federal Open Data Policy, data scientists are needed to improve usability for and make sense of that data. As with many IT jobs, the growing need for data scientists is exceeding the supply of available applicants. Even when talent is available, governments usually can’t afford the average six-figure price tag.

Due to this uphill talent battle, the public sector is beginning to take advantage of emerging tools that make it easier for non-technical employees to analyze, visualize, and make an impact with data. By empowering these “citizen data scientists,” local governments can circumvent the skills gap war.

Wanted: data scientist

While governments may have a tough time attracting top tech talent, this issue reaches far beyond the public sector. Data management and analysis is cited as one of the top seven IT skills gaps organizations face today, according to a recent CompTIA report. Tech companies have tried quick fix solutions to solve the skills gap like using the H1-B visa program or IT offshoring, but neither have proven to be sustainable options for creating a pipeline of data scientists.

Talent availability isn’t the only obstacle the public sector faces. The average data scientist salary costs employers more than $113,000 a year; it doesn’t quite compare to the local government payout for a similar job title, averaging $78,000. In a year where, at any given time, 11 states were without budgets, governments can barely compete with private sector payroll numbers.

As a result of these hiring difficulties, the public sector is using technology to level the playing field and better meet the needs of its constituents. Public servants use data to drive decision-making, and with this, we’ve seen the emergence of the citizen data scientist.

The emergence of the citizen data scientist

To manage growing volumes of data emerging each day, governments can offer tools that empower current employees to harness and understand data. Here are a few common mistakes the public sector faces when non-technical employees take on the day-to-day duties of a data scientist:

Assuming all software is the same – While anyone can experiment with data analytics software like Excel or Tableau, access to the programs does not make one a data scientist. A basic understanding of Photoshop doesn’t make the user a graphic designer, and the same goes for Excel and data scientists. If your organization is shifting the responsibilities of the vacant data scientist role to a current employee, consider using software created for people of varying skill sets.

“Younger employees are better with tech” syndrome – Along with gender discrimination, ageism is one of the largest problems in the tech industry. Don’t perpetuate this stereotype by delegating technical tasks to the recent graduates or Millennials in your office. Offer employee trainings for any data visualization software that your organization decides to implement. Different people will need to wear the citizen data scientist hat depending on the project. With data being created and collected more and more each day, everyone can benefit from flexing their data scientist skills.

The need for and the prevalence of citizen data scientists is on the rise. Gartner predicts that automation will decrease demand for specialized data scientists, leading to “citizen data scientists” surpassing them in advanced analysis by 2019. Government agencies are keen to this trend. As the key holder to masses of public data, it’s essential for public agencies to cultivate citizen data scientists for a more democratic approach to big data.

Adnan Mahmud is the founder and CEO of integrated civic data hub company LiveStories.

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